A Dynamic Robust Restoration Framework for Unbalanced Power Distribution Networks

Junjun Xu, Zaijun Wu, Xinghuo Yu, Sheng Cheng, Qinran Hu, Qiuwei Wu

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The increasing penetration of photovoltaic (PV) generators has led to a reduction in the effectiveness of existing strategies for restoring the power distribution network. This paper proposes a dynamic robust restoration (DRR) framework for the recovery of outage power considering uncertain PV outputs and demands. This framework is presented in two subsequent steps. In the first step, optimal decisions regarding the network configurations are generated. The second step then computes the modified dynamic Distflow equations and constraints under consideration of the worst operating conditions over the associated uncertainty sets with the aim of maximizing the recovery of outage power. The DRR model is formulated as a bi-level mixed-integer linear programming problem. A decomposition algorithm in a master-sub structure is used to solve the resulting system. The results of case studies show that the proposed DRR model yields obvious advantages over the existing deterministic dynamic restoration model in terms of robustness against system uncertainties.
Original languageEnglish
JournalI E E E Transactions on Industrial Informatics
Issue number10
Pages (from-to)6301 - 6312
Publication statusPublished - 2020


  • Distributed generators
  • Dynamic restoration
  • Power distribution networks
  • Robust optimization

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